Extracellular proximity labeling reveals an expanded interactome for the matrisome protein TIMP2
Ontology highlight
ABSTRACT:
PROVIDER: PRJNA1061234 | ENA |
REPOSITORIES: ENA
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| SRR27431457_1.fastq.gz | Fastqsanger.gz | |||
| SRR27431457_2.fastq.gz | Fastqsanger.gz | |||
| SRR27431458_1.fastq.gz | Fastqsanger.gz | |||
| SRR27431458_2.fastq.gz | Fastqsanger.gz | |||
| SRR27431459_1.fastq.gz | Fastqsanger.gz |
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Project description:Classical methods of investigating protein-protein interactions (PPIs) are generally performed in non-living systems, yet in recent years new technologies utilizing proximity labeling (PL) have given researchers the tools to explore proximal PPIs in living systems. PL has distinct advantages over traditional protein interactome studies, such as the ability to identify weak and transient interactions in vitro and in vivo. Most PL studies are performed on targets within or on the cell membrane. We have adapted the original PL method to investigate PPIs within the extracellular compartment, using both BioID2 and TurboID, that we term extracellular PL (ePL). To demonstrate the utility of this modified technique, we investigate the interactome of the widely expressed matrisome protein Tissue inhibitors of metalloproteinases 2 (TIMP2). Tissue inhibitors of metalloproteinases (TIMPs) are a family of multi-functional proteins that were initially defined by their ability to inhibit the enzymatic activity of metalloproteinases (MPs), the major mediators of extracellular matrix (ECM) breakdown and turnover. TIMP2 exhibits a broad expression profile and is often abundant in both normal and diseased tissues. Understanding the functional transformation of matrisome regulators, like TIMP2, during the evolution of tissue microenvironments associated with disease progression is essential for the development of ECM targeted therapeutics. Using carboxyl- and amino-terminal fusion proteins of TIMP2 with BioID2 and TurboID, we describe the TIMP2 proximal interactome. We also illustrate how the TIMP2 interactome changes in the presence of different stimuli, in different cell types, in unique culture conditions (2D vs 3D), and with different reaction kinetics (BioID2 vs. TurboID); demonstrating the power of this technique versus classical PPI methods. We propose that the screening of matrisome targets in disease models using ePL will reveal new therapeutic targets for further comprehensive studies.
2024-01-09 | GSE252575 | GEO
Project description:Classical methods of investigating protein-protein interactions (PPIs) are generally performed in non-living systems, yet in recent years new technologies utilizing proximity labeling (PL) have given researchers the tools to explore proximal PPIs in living systems. PL has distinct advantages over traditional protein interactome studies, such as the ability to identify weak and transient interactions in vitro and in vivo. Most PL studies are performed on targets within the cell or on the cell membrane. We have adapted the original PL method to investigate PPIs within the extracellular compartment, using both BioID2 and TurboID, that we term extracellular PL (ePL). To demonstrate the utility of this modified technique, we investigate the interactome of the widely expressed matrisome protein tissue inhibitor of metalloproteinases 2 (TIMP2). Tissue inhibitors of metalloproteinases (TIMPs) are a family of multi-functional proteins that were initially defined by their ability to inhibit the enzymatic activity of metalloproteinases (MPs), the major mediators of extracellular matrix (ECM) breakdown and turnover. TIMP2 exhibits a broad expression profile and is often abundant in both normal and diseased tissues. Understanding the functional transformation of matrisome regulators, like TIMP2, during the evolution of tissue microenvironments associated with disease progression is essential for the development of ECM-targeted therapeutics. Using carboxyl- and amino-terminal fusion proteins of TIMP2 with BioID2 and TurboID, we describe the TIMP2 proximal interactome. We also illustrate how the TIMP2 interactome changes in the presence of different stimuli, in different cell types, in unique culture conditions (2D vs 3D), and with different reaction kinetics (BioID2 vs. TurboID); demonstrating the power of this technique versus classical PPI methods. We propose that the screening of matrisome targets in disease models using ePL will reveal new therapeutic targets for further comprehensive studies.
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Project description:Off-the-shelf proximity labeling
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Project description:BAP-seq proximity labeling of subcellular compartments
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Project description:APEX2 RNA proximity labeling is a powerful method for determining localized RNAs in vivo. APEX2 RNA proximity labeling was adapted to bacterial cells, using an APEX2 fusion to the core scaffold of BR-bodies, RNase E. As a control, APEX2 was also fused to a variant of RNase E that lacks its C-terminal IDR and is unable to form BR-bodies, RNase E delta CTD. RNA proximity labeling was performed, and we observed a similar pattern of enriched RNAs to density centrifugation isolated BR-bodies (Al-Husini et al. Mol Cell 2020).
2025-05-31 | GSE297938 | GEO
Project description:Mapping the spatial organization of proteins and cellular interactions is crucial for understanding their biological functions. Herein, we report a biocompatible, multi-functional luminescence-activated proximity labeling (LAP) strategy for profiling subcellular proteomes and cell-cell interactions in live cells and animals. Our method capitalizes on fusing the photocatalyst miniSOG to NanoLuc luciferase, whose bioluminescence activates miniSOG via a resonance energy transfer mechanism, generating reactive oxygen species in situ to mediate proximity labeling. We achieved local transcriptome profiling by combining LAP with next-generation sequencing.
2025-05-10 | GSE276085 | GEO
Project description:Bioluminescence-activated proximity labeling for spatial multi-omics
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Project description:Assessment of the TIMP2 interactome in HT1080 and HS-5 cells using proximity labeling (TurboID and BioID2). File designations included in the excel spreadsheet.
Metadata - file will be added when upload bugs are fixed. Comma separated metadata below:
File Name Prefix,Cell Line,Biotin Ligase,Treatment,Label,x Identity / Notes,
P1301-x-EXP_1,HT1080,TurboID,Untreated,N/A,1 = Control; 2 = TurboID; 3 = TIMP2-TurboID; 4 = TurboID-TIMP2,
P1301-x-EXP_2,HT1080,TurboID,Untreated,N/A,5 = Control; 6 = TurboID; 7 = TIMP2-TurboID; 8 = TurboID-TIMP2,
P1314-x-EXP_5,HT1080,TurboID,Concanavalin A treated,N/A,1 = Control; 2 = TurboID; 3 = TIMP2-TurboID; 4 = TurboID-TIMP2,
P1314-x-EXP_6,HT1080,TurboID,Concanavalin A treated,N/A,5 = Control; 6 = TurboID; 7 = TIMP2-TurboID; 8 = TurboID-TIMP2,
P1314-x-EXP_7,HT1080,BioID2,Untreated,N/A,9 = Control; 10 = BioID2; 11 = BioID2-TIMP2; 12 = TIMP2-BioID2,
P1314-x-EXP_8,HT1080,BioID2,Untreated,N/A,13 = Control; 14 = BioID2; 15 = BioID2-TIMP2; 16 = TIMP2-BioID2,
P1333-EXP_9-x,HT1080,TurboID,3D culture (spheroid),N/A,1 = Control; 2 = TurboID; 3 = TIMP2-TurboID; 4 = TurboID-TIMP2,
P1407-x-EXP_21,HT1080,TurboID,3D culture (spheroid),N/A,1 = TurboID; 2 = TIMP2-TurboID; 3 = TurboID-TIMP2,
P1333-EXP_10-x,HT1080,TurboID,PMA treated,N/A,1 = Control; 2 = TurboID; 3 = TIMP2-TurboID; 4 = TurboID-TIMP2,
P1352-EX13-x,HT1080,TurboID,PMA treated,N/A,1 = Control; 2 = TurboID; 3 = TIMP2-TurboID; 4 = TurboID-TIMP2,
P1358-1_126-129C,HS-5,TurboID,Untreated,TMT,126 = Control; 127C = TurboID; 128C = TIMP2-TurboID; 129C = TurboID-TIMP2,
P1358-2_127N-130N,HS-5,TurboID,Untreated,TMT,127N = Control; 128N = TurboID; 129N = TIMP2-TurboID; 130N = TurboID-TIMP2
2024-08-18 | MSV000095637 | MassIVE